{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 语义分割和数据集\n",
    "\n",
    "最重要的语义分割数据集之一是[Pascal VOC2012](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "origin_pos": 4,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import torch\n",
    "import torchvision\n",
    "from d2l import torch as d2l\n",
    "\n",
    "d2l.DATA_HUB['voc2012'] = (d2l.DATA_URL + 'VOCtrainval_11-May-2012.tar',\n",
    "                           '4e443f8a2eca6b1dac8a6c57641b67dd40621a49')\n",
    "\n",
    "voc_dir = d2l.download_extract('voc2012', 'VOCdevkit/VOC2012')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "将所有输入的图像和标签读入内存"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "origin_pos": 7,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def read_voc_images(voc_dir, is_train=True):\n",
    "    \"\"\"读取所有VOC图像并标注。\"\"\"\n",
    "    txt_fname = os.path.join(voc_dir, 'ImageSets', 'Segmentation',\n",
    "                             'train.txt' if is_train else 'val.txt')\n",
    "    mode = torchvision.io.image.ImageReadMode.RGB\n",
    "    with open(txt_fname, 'r') as f:\n",
    "        images = f.read().split()\n",
    "    features, labels = [], []\n",
    "    for i, fname in enumerate(images):\n",
    "        features.append(\n",
    "            torchvision.io.read_image(\n",
    "                os.path.join(voc_dir, 'JPEGImages', f'{fname}.jpg')))\n",
    "        labels.append(\n",
    "            torchvision.io.read_image(\n",
    "                os.path.join(voc_dir, 'SegmentationClass', f'{fname}.png'),\n",
    "                mode))\n",
    "    return features, labels\n",
    "\n",
    "train_features, train_labels = read_voc_images(voc_dir, True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "绘制前5个输入图像及其标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "origin_pos": 10,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 5\n",
    "imgs = train_features[0:n] + train_labels[0:n]\n",
    "imgs = [img.permute(1, 2, 0) for img in imgs]\n",
    "d2l.show_images(imgs, 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "列举RGB颜色值和类名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "origin_pos": 12,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "VOC_COLORMAP = [[0, 0, 0], [128, 0, 0], [0, 128, 0], [128, 128, 0],\n",
    "                [0, 0, 128], [128, 0, 128], [0, 128, 128], [128, 128, 128],\n",
    "                [64, 0, 0], [192, 0, 0], [64, 128, 0], [192, 128, 0],\n",
    "                [64, 0, 128], [192, 0, 128], [64, 128, 128], [192, 128, 128],\n",
    "                [0, 64, 0], [128, 64, 0], [0, 192, 0], [128, 192, 0],\n",
    "                [0, 64, 128]]\n",
    "\n",
    "VOC_CLASSES = [\n",
    "    'background', 'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus',\n",
    "    'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike',\n",
    "    'person', 'potted plant', 'sheep', 'sofa', 'train', 'tv/monitor']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "查找标签中每个像素的类索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "origin_pos": 15,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def voc_colormap2label():\n",
    "    \"\"\"构建从RGB到VOC类别索引的映射。\"\"\"\n",
    "    colormap2label = torch.zeros(256**3, dtype=torch.long)\n",
    "    for i, colormap in enumerate(VOC_COLORMAP):\n",
    "        colormap2label[(colormap[0] * 256 + colormap[1]) * 256 +\n",
    "                       colormap[2]] = i\n",
    "    return colormap2label\n",
    "\n",
    "def voc_label_indices(colormap, colormap2label):\n",
    "    \"\"\"将VOC标签中的RGB值映射到它们的类别索引。\"\"\"\n",
    "    colormap = colormap.permute(1, 2, 0).numpy().astype('int32')\n",
    "    idx = ((colormap[:, :, 0] * 256 + colormap[:, :, 1]) * 256 +\n",
    "           colormap[:, :, 2])\n",
    "    return colormap2label[idx]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "例如"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "origin_pos": 17,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[0, 0, 0, 0, 0, 0, 0, 0, 0, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 1, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 0, 1, 1]]),\n",
       " 'aeroplane')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = voc_label_indices(train_labels[0], voc_colormap2label())\n",
    "y[105:115, 130:140], VOC_CLASSES[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "使用图像增广中的随机裁剪，裁剪输入图像和标签的相同区域"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "origin_pos": 22,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def voc_rand_crop(feature, label, height, width):\n",
    "    \"\"\"随机裁剪特征和标签图像。\"\"\"\n",
    "    rect = torchvision.transforms.RandomCrop.get_params(\n",
    "        feature, (height, width))\n",
    "    feature = torchvision.transforms.functional.crop(feature, *rect)\n",
    "    label = torchvision.transforms.functional.crop(label, *rect)\n",
    "    return feature, label\n",
    "\n",
    "imgs = []\n",
    "for _ in range(n):\n",
    "    imgs += voc_rand_crop(train_features[0], train_labels[0], 200, 300)\n",
    "\n",
    "imgs = [img.permute(1, 2, 0) for img in imgs]\n",
    "d2l.show_images(imgs[::2] + imgs[1::2], 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "自定义语义分割数据集类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "origin_pos": 25,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "class VOCSegDataset(torch.utils.data.Dataset):\n",
    "    \"\"\"一个用于加载VOC数据集的自定义数据集。\"\"\"\n",
    "    def __init__(self, is_train, crop_size, voc_dir):\n",
    "        self.transform = torchvision.transforms.Normalize(\n",
    "            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
    "        self.crop_size = crop_size\n",
    "        features, labels = read_voc_images(voc_dir, is_train=is_train)\n",
    "        self.features = [\n",
    "            self.normalize_image(feature)\n",
    "            for feature in self.filter(features)]\n",
    "        self.labels = self.filter(labels)\n",
    "        self.colormap2label = voc_colormap2label()\n",
    "        print('read ' + str(len(self.features)) + ' examples')\n",
    "\n",
    "    def normalize_image(self, img):\n",
    "        return self.transform(img.float())\n",
    "\n",
    "    def filter(self, imgs):\n",
    "        return [\n",
    "            img for img in imgs if (img.shape[1] >= self.crop_size[0] and\n",
    "                                    img.shape[2] >= self.crop_size[1])]\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        feature, label = voc_rand_crop(self.features[idx], self.labels[idx],\n",
    "                                       *self.crop_size)\n",
    "        return (feature, voc_label_indices(label, self.colormap2label))\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "读取数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "origin_pos": 27,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1114 examples\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1078 examples\n"
     ]
    }
   ],
   "source": [
    "crop_size = (320, 480)\n",
    "voc_train = VOCSegDataset(True, crop_size, voc_dir)\n",
    "voc_test = VOCSegDataset(False, crop_size, voc_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "origin_pos": 30,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([64, 3, 320, 480])\n",
      "torch.Size([64, 320, 480])\n"
     ]
    }
   ],
   "source": [
    "batch_size = 64\n",
    "train_iter = torch.utils.data.DataLoader(\n",
    "    voc_train, batch_size, shuffle=True, drop_last=True,\n",
    "    num_workers=d2l.get_dataloader_workers())\n",
    "for X, Y in train_iter:\n",
    "    print(X.shape)\n",
    "    print(Y.shape)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "整合所有组件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "origin_pos": 33,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def load_data_voc(batch_size, crop_size):\n",
    "    \"\"\"加载VOC语义分割数据集。\"\"\"\n",
    "    voc_dir = d2l.download_extract('voc2012',\n",
    "                                   os.path.join('VOCdevkit', 'VOC2012'))\n",
    "    num_workers = d2l.get_dataloader_workers()\n",
    "    train_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(True, crop_size, voc_dir), batch_size, shuffle=True,\n",
    "        drop_last=True, num_workers=num_workers)\n",
    "    test_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(False, crop_size, voc_dir), batch_size, drop_last=True,\n",
    "        num_workers=num_workers)\n",
    "    return train_iter, test_iter"
   ]
  }
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